run_analysis.R

library(plyr)

x_train <- read.table("train/X_train.txt")
y_train <- read.table("train/y_train.txt")
subject_train <- read.table("train/subject_train.txt")

x_test <- read.table("test/X_test.txt")
y_test <- read.table("test/y_test.txt")
subject_test <- read.table("test/subject_test.txt")

# create x data set
x_data <- rbind(x_train, x_test)

# create y data set
y_data <- rbind(y_train, y_test)

# create subject data set
subject_data <- rbind(subject_train, subject_test)

features <- read.table("features.txt")

mean_and_std_features <- grep("-(mean|std)\\(\\)", features[, 2])

x_data <- x_data[, mean_and_std_features]

names(x_data) <- features[mean_and_std_features, 2]

activities <- read.table("activity_labels.txt")

y_data[, 1] <- activities[y_data[, 1], 2]

names(y_data) <- "activity"
names(subject_data) <- "subject"

all_data <- cbind(x_data, y_data, subject_data)
averages_data <- ddply(all_data, .(subject, activity), function(x) colMeans(x[, 1:66]))
write.table(averages_data, "averages_data.txt", row.name=FALSE)